Demystifying estimands in cluster-randomised trials.
Stat Methods Med Res
; 33(7): 1211-1232, 2024 Jul.
Article
in En
| MEDLINE
| ID: mdl-38780480
ABSTRACT
Estimands can help clarify the interpretation of treatment effects and ensure that estimators are aligned with the study's objectives. Cluster-randomised trials require additional attributes to be defined within the estimand compared to individually randomised trials, including whether treatment effects are marginal or cluster-specific, and whether they are participant- or cluster-average. In this paper, we provide formal definitions of estimands encompassing both these attributes using potential outcomes notation and describe differences between them. We then provide an overview of estimators for each estimand, describe their assumptions, and show consistency (i.e. asymptotically unbiased estimation) for a series of analyses based on cluster-level summaries. Then, through a re-analysis of a published cluster-randomised trial, we demonstrate that the choice of both estimand and estimator can affect interpretation. For instance, the estimated odds ratio ranged from 1.38 (p = 0.17) to 1.83 (p = 0.03) depending on the target estimand, and for some estimands, the choice of estimator affected the conclusions by leading to smaller treatment effect estimates. We conclude that careful specification of the estimand, along with an appropriate choice of estimator, is essential to ensuring that cluster-randomised trials address the right question.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Randomized Controlled Trials as Topic
Limits:
Humans
Language:
En
Journal:
Stat Methods Med Res
/
Stat. methods med. res
/
Statistical methods in medical research
Year:
2024
Document type:
Article
Country of publication: